Face recognition using Dual Linear Regression based Classification
Yuan Wang · 2016
This project discusses a face recognition algorithm that uses Dual Linear Regression based Classification (DLRC) and a voting approach.Each face image used is first converted into a cluster of images; each image in the cluster is obtained by shifting the original image a few pixels.The similarity of a pair of face images can be measured by comparing the distance between the corresponding image clusters, which is calculated using DLRC approach.To further improve performance, each cluster of images.representing a single face image.is then partitioned into a union of clusters of sub images.DLRC is t hen used to measure similarities between corresponding sub-image clusters to provide temporary identity decisions: a voting approach is applied to make final conclusions.Vve have carried out experiments on a benchmark dataset for face recognition.The result demonstrates that the proposed approach works best in certain simple situations.while its performance is also comparable to known algorithms in complicated situations.